IEEE Trans Vis Comput Graph - Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming.

Tópicos

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Resumo

Direct projection of 3D branching structures, such as networks of cables, blood vessels, or neurons onto a 2D image creates the illusion of intersecting structural parts and creates challenges for understanding and communication. We present a method for visualizing such structures, and demonstrate its utility in visualizing the abdominal aorta and its branches, whose tomographic images might be obtained by computed tomography or magnetic resonance angiography, in a single 2D stylistic image, without overlaps among branches. The visualization method, termed uncluttered single-image visualization (USIV), involves optimization of geometry. This paper proposes a novel optimization technique that utilizes an interesting connection of the optimization problem regarding USIV to the protein structure prediction problem. Adopting the integer linear programming-based formulation for the protein structure prediction problem, we tested the proposed technique using 30 visualizations produced from five patient scans with representative anatomical variants in the abdominal aortic vessel tree. The novel technique can exploit commodity-level parallelism, enabling use of general-purpose graphics processing unit (GPGPU) technology that yields a significant speedup. Comparison of the results with the other optimization technique previously reported elsewhere suggests that, in most aspects, the quality of the visualization is comparable to that of the previous one, with a significant gain in the computation time of the algorithm.

Resumo Limpo

direct project d branch structur network cabl blood vessel neuron onto d imag creat illus intersect structur part creat challeng understand communic present method visual structur demonstr util visual abdomin aorta branch whose tomograph imag might obtain comput tomographi magnet reson angiographi singl d stylist imag without overlap among branch visual method term unclutt singleimag visual usiv involv optim geometri paper propos novel optim techniqu util interest connect optim problem regard usiv protein structur predict problem adopt integ linear programmingbas formul protein structur predict problem test propos techniqu use visual produc five patient scan repres anatom variant abdomin aortic vessel tree novel techniqu can exploit commoditylevel parallel enabl use generalpurpos graphic process unit gpgpu technolog yield signific speedup comparison result optim techniqu previous report elsewher suggest aspect qualiti visual compar previous one signific gain comput time algorithm

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